title: A high performance cloud computing platform for mRNA analysis.
abstract: Multiclass classification is an important technique to many complex bioinformatics problems. However, their performance is limited by the computation power. Based on the Apache Hadoop design framework, this study proposes a two layer architecture that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have reduced 86.55% features and raised accuracy from 97.53% to 98.03%. With a user-friendly web interface, the system provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of bioinformatics data.
authors.forename: Feng-Seng
authors.initials: FS
authors.lastname: Lin
authors.forename: Chia-Ping
authors.initials: CP
authors.lastname: Shen
authors.forename: Hsiao-Ya
authors.initials: HY
authors.lastname: Sung
authors.forename: Yan-Yu
authors.initials: YY
authors.lastname: Lam
authors.forename: Jeng-Wei
authors.initials: JW
authors.lastname: Lin
authors.forename: Feipei
authors.initials: F
authors.lastname: Lai
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D012333:RNA, Messenger / Q000032:analysis* / Q000235:genetics; D013997:Time Factors
chemical_list: D012333:RNA, Messenger